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Can I run this LLM?

Can a NVIDIA H100 SXM (80GB) run Ornith 1.0 35B (MoE)?

Ornith · MIT · estimated for a 80.0 GB machine at 4K context.

Yes — it runs great.

Runs great

Best fit: Ornith 1.0 35B (MoE) at Q8_0 · 36.9 GB weights · 247–371 tok/s on a NVIDIA H100 SXM (80GB).

Arena Text Overall · style-controlled

UnratedNo exact match

No reviewed exact Arena match

No reviewed exact model/configuration match in the Arena Text Overall style-controlled snapshot. No family or editorial score is substituted. Local quantization quality is unmeasured.

Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh

Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986

Total memory at 4K context
37.8 GB
Weights + KV cache + runtime overhead
Estimated generation
247–371 tok/s
Estimated first token
~0.1s

Every quantization on this machine

On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.

Ornith 1.0 35B (MoE) quantizations on NVIDIA H100 SXM (80GB), estimated at 4K context. Weights and total memory are shown separately.
QuantWeightsTotal memorySpeedFit
Q2_K12.3 GB13.1 GB314–471 tok/sRuns great
Q3_K_M16.7 GB17.6 GB299–449 tok/sRuns great
Q4_K_M22.1 GB23.0 GB283–425 tok/sRuns great
Q5_K_M26.5 GB27.3 GB271–407 tok/sRuns great
Q6_K29.3 GB30.2 GB264–397 tok/sRuns great
Q8_036.9 GB37.8 GB247–371 tok/sRuns great
FP1669.4 GB70.3 GB193–289 tok/sTight / slow
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